One of the most recent and profitable applications in the telecommunications industry, mobile telephony has now reached a stage where it is widely available to the public. As a result, the quality of such mobile telephony services is of special concern for companies seeking to remain competitive in the market.
In that regard, mobile telephone calls frequently originate from noisy environments. Prior art noise suppression systems, such as that discussed in an article by Hermansky et al. entitled "Speech Enhancement Based On Temporal Processing", IEEE ICASSP Conference Proceedings, pp. 405-408, Detroit, Mich., 1995, disclose speech enhancement techniques for suppressing such noise in which compressed time trajectories of power spectral components of short-time spectrum of corrupted speech are processed by a filter bank with finite impulse response (FIR) filters designed on parallel recordings of clean and noisy data.
However, the "background noise" in mobile communications described above generally exhibits characteristics which change from one call to the next. In contrast, the prior art noise suppression techniques described above are noise-specific. As a result, such techniques are most efficient on disturbances similar to those present in the training data.
Thus, there exists a need for an improved speech enhancement method and system. Such a method and system would use a priori knowledge concerning speech temporal properties under different noise conditions so that only an estimate of the noise level would be required to effectively enhance a speech signal. In contrast to the prior art, such a speech enhancement method and system would thus provide for adaptive filtering by accounting for the noise variations present in mobile communications.